--- a/fastqc_report.Rmd	Mon Oct 16 21:33:31 2017 -0400
+++ b/fastqc_report.Rmd	Wed Oct 18 22:06:39 2017 -0400
@@ -1,383 +1,72 @@
 ---
-title: "Fastqc report: short reads quality evaluation"
-author: "Ming Chen"
-output: html_document
+title: 'HTML report title'
+output:
+    html_document:
+      number_sections: true
+      toc: true
+      theme: cosmo
+      highlight: tango
 ---
 
-```{r setup, include=FALSE}
-knitr::opts_chunk$set(echo=ECHO, warning=FALSE, message=FALSE)
-library(plyr)
-library(stringr)
-library(dplyr)
-library(highcharter)
-library(DT)
-library(reshape2)
-library(plotly)
-library(formattable)
-library(htmltools)
+```{r setup, include=FALSE, warning=FALSE, message=FALSE}
+knitr::opts_chunk$set(
+  echo = ECHO
+)
 ```
 
 
-```{bash 'create output directory', echo=FALSE}
-# create extra files directory. very important!
-mkdir REPORT_OUTPUT_DIR
-```
+# Fastqc Analysis
 
-# Fastqc analysis
-```{bash 'copy data to working directory', echo=FALSE}
-# Copy uploaded data to the working directory
+* Copy fastq files to job working directory
+
+```{bash 'copy files'}
 for f in $(echo READS | sed "s/,/ /g")
 do
     cp $f ./
 done
 ```
 
+* Run fastqc
 
-```{bash 'run fastqc', echo=FALSE}
+```{bash 'run fastqc'}
 for r in $(ls *.dat)
 do
-    fastqc -o REPORT_OUTPUT_DIR $r > /dev/null 2>&1
+    fastqc -o REPORT_DIR $r > /dev/null 2>&1
 done
 ```
 
-## Fastqc html reports
+* Create links to original HTML reports
 
-Below are links to ***Fastqc*** original html reports.
 ```{r 'html report links'}
 html_report_list = list()
-html_files = list.files('REPORT_OUTPUT_DIR', pattern = '.*html')
+html_files = list.files('REPORT_DIR', pattern = '.*html')
 for (i in html_files) {
   html_report_list[[i]] = tags$li(tags$a(href=i, i))
 }
 tags$ul(html_report_list)
 ```
 
-
-## Parsing fastqc data
-
-```{bash echo=FALSE}
-##==== copy fastqc generated zip files from report output directory to job work directory ==
-cp -r REPORT_OUTPUT_DIR/*zip ./
-
-# create a file to store data file paths
-echo "sample_id,file_path" > PWF_file_paths.txt # Pass, Warning, Fail
-echo "sample_id,file_path" > PBQS_file_paths.txt # Per Base Quality Score
-echo "sample_id,file_path" > PSQS_file_paths.txt # Per Sequence Quality Score
-echo "sample_id,file_path" > PSGC_file_paths.txt # Per Sequence GC Content
-echo "sample_id,file_path" > PBSC_file_paths.txt # Per Base Sequence Content
-echo "sample_id,file_path" > PBNC_file_paths.txt # Per Base N Content
-echo "sample_id,file_path" > SDL_file_paths.txt # Sequence Duplication Level
-echo "sample_id,file_path" > SLD_file_paths.txt # Sequence Length Distribution
-echo "sample_id,file_path" > KMC_file_paths.txt # Kmer Content
-
-for i in $(ls *.zip)
-do
-    BASE=$(echo $i | sed 's/\(.*\)\.zip/\1/g')
-    echo $BASE
-    unzip ${BASE}.zip > /dev/null 2>&1
-    
-    ##====== pass,warning,fail (WSF) =============
-    awk '/^>>/ {print}' "$BASE"/fastqc_data.txt | grep -v 'END_MODULE' | sed 's/>>//' > "$BASE"-PWF.txt
-    echo "${BASE},${BASE}-PWF.txt" >> PWF_file_paths.txt
+# Fastqc output summary
 
-    ##====== per base quality scores (PBQS) ======
-    awk '/^>>Per base sequence quality/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBQS.txt
-    echo "${BASE},${BASE}-PBQS.txt" >> PBQS_file_paths.txt
-
-    ##====== per sequence quality scores (PSQS)
-    awk '/^>>Per sequence quality scores/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PSQS.txt
-    echo "${BASE},${BASE}-PSQS.txt" >> PSQS_file_paths.txt
-
-    ##====== Per sequence GC content (PSGC)
-    awk '/^>>Per sequence GC content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PSGC.txt
-    echo "${BASE},${BASE}-PSGC.txt" >> PSGC_file_paths.txt
-    
-    ##====== Per Base Sequence Content (PBSC)
-    awk '/^>>Per base sequence content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBSC.txt
-    echo "${BASE},${BASE}-PBSC.txt" >> PBSC_file_paths.txt
-    
-    ##====== Per Base N Content (PBNC)
-    awk '/^>>Per base N content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBNC.txt
-    echo "${BASE},${BASE}-PBNC.txt" >> PBNC_file_paths.txt
-    
-    ##====== Sequence Duplication Level (SDL)
-    awk '/^>>Sequence Duplication Levels/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-SDL.txt
-    echo "${BASE},${BASE}-SDL.txt" >> SDL_file_paths.txt
-    
-    ##====== Sequence Length Distribution (SLD)
-    awk '/^>>Sequence Length Distribution/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-SLD.txt
-    echo "${BASE},${BASE}-SLD.txt" >> SLD_file_paths.txt
-    
-    ##====== Kmer Content ============
-    awk '/^>>Kmer Content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-KMC.txt
-    echo "${BASE},${BASE}-KMC.txt" >> KMC_file_paths.txt
-    
-done
-```
+* Define a function to extract outputs for each module from fastqc output
 
-
-## Evaluation Overview
-
-```{r 'overview'}
-PWF_file_paths = read.csv('PWF_file_paths.txt',
-                           header = TRUE, stringsAsFactors = FALSE)
-rm('PWF_df')
-for(i in 1:nrow(PWF_file_paths)) {
-  file_path = PWF_file_paths[i,2]
-  pwf_df = read.csv(file_path,
-                     sep='\t', header=FALSE, stringsAsFactors = FALSE)
-  colnames(pwf_df) = c('item', PWF_file_paths[i,1])
-  if (!exists('PWF_df')) {
-    PWF_df = pwf_df
-  } else {
-    PWF_df = cbind(PWF_df, pwf_df[,2,drop=FALSE])
-  }
-}
-```
-
-```{r}
-my_icon = c('ok', 'remove', 'star')
-names(my_icon) = c('pass', 'fail', 'warn')
-evaluate_list = list()
-for (i in colnames(PWF_df)[-1]) {
-  evaluate_list[[i]] = formatter(
-      "span", 
-      style = x ~ style("background-color" = ifelse(x =='pass', '#9CD027', ifelse(x == 'fail', '#CC0000', '#FF4E00')), 
-                        "color" = "white",
-                        "width" = "50px",
-                        "float" = "left",
-                        "padding-right" = "5px")
-    )
-}
-
-formattable(PWF_df, evaluate_list)
-```
-
-
-## Per Base Quality Scores
-
-```{r}
-PBQS_df = data.frame()
-PBQS_file_paths = read.csv('PBQS_file_paths.txt',
-                           header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBQS_file_paths)) {
-  # file_path = paste0('REPORT_OUTPUT_DIR/', PBQS_file_paths[i,2])
-  file_path = PBQS_file_paths[i,2]
-  pbqs_df = read.csv(file_path,
-                     sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
-    mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
-           Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
-  (function (df) {
-    df1 = select(df, -Base2)
-    df2 = select(df, -Base1) %>% filter(Base2 != '')
-    colnames(df1) = c(colnames(df1)[1:7], 'Base')
-    colnames(df2) = c(colnames(df2)[1:7], 'Base')
-    res = rbind(df1, df2) %>% arrange(Base)
-    return(res)
-  })
-  pbqs_df$sample_id = rep(PBQS_file_paths[i,1], nrow(pbqs_df))
-  PBQS_df = rbind(PBQS_df, pbqs_df)
+```{r 'function definition'}
+extract_data_module = function(fastqc_data, module_name) {
+  f = readLines(fastqc_data)
+  start_line = grep(module_name, f)
+  end_module_lines = grep('END_MODULE', f)
+  end_line = end_module_lines[which(end_module_lines > start_line)[1]]
+  module_data = f[(start_line+1):(end_line-1)]
+  writeLines(module_data, 'temp.txt')
+  read.csv('temp.txt', sep = '\t')
 }
 ```
 
-
-```{r}
-# datatable(PBQS_df)
-max_phred = max(PBQS_df$Mean) + 10
-hchart(PBQS_df, "line", hcaes(x = Base, y = Mean, group = sample_id)) %>%
-  hc_title(
-    text = "Per Base Quality Score"
-  ) %>%
-  hc_yAxis(
-    title = list(text = "Mean Base Quality Score"),
-    min = 0,
-    max = max_phred,
-    plotLines = list(
-      list(label = list(text = "Phred Score = 27"),
-           width = 2,
-           dashStyle = "dash",
-           color = "green",
-           value = 27),
-      list(label = list(text = "Phred Score = 20"),
-           width = 2,
-           color = "red",
-           value = 20)
-    )
-  ) %>% 
-  hc_exporting(enabled = TRUE)
-```
-
-
-## Per Base N Content
+## 
 
-```{r}
-PBNC_df = data.frame()
-PBNC_file_paths = read.csv('PBNC_file_paths.txt',
-                           header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBNC_file_paths)) {
-  # file_path = paste0('REPORT_OUTPUT_DIR/', PBNC_file_paths[i,2])
-  file_path = PBNC_file_paths[i,2]
-  pbnc_df = read.csv(file_path,
-                     sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
-    mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
-           Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
-  (function (df) {
-    df1 = select(df, -Base2)
-    df2 = select(df, -Base1) %>% filter(Base2 != '')
-    colnames(df1) = c(colnames(df1)[1:2], 'Base')
-    colnames(df2) = c(colnames(df2)[1:2], 'Base')
-    res = rbind(df1, df2) %>% arrange(Base)
-    return(res)
-  })
-  pbnc_df$sample_id = rep(PBNC_file_paths[i,1], nrow(pbnc_df))
-  PBNC_df = rbind(PBNC_df, pbnc_df)
-}
-```
-
+# Session Info
 
-```{r}
-PBNC_df$N.Count = PBNC_df$N.Count * 100
-max_phred = max(PBNC_df$N.Count) + 5
-hchart(PBNC_df, "line", hcaes(x = as.character(Base), y = N.Count, group = sample_id)) %>%
-  hc_title(
-    text = "Per Base N Content"
-  ) %>%
-  hc_xAxis(
-    title = list(text = "Base Position")
-  ) %>%
-  hc_yAxis(
-    title = list(text = "N %"),
-    plotLines = list(
-      list(label = list(text = "N = 5%"),
-           width = 2,
-           dashStyle = "dash",
-           color = "red",
-           value = 5)
-    )
-  ) %>% 
-  hc_exporting(enabled = TRUE)
-```
-
-
-
-
-## Per Sequence Quality Scores
-
-```{r}
-PSQS_df = data.frame()
-PSQS_file_paths = read.csv('PSQS_file_paths.txt', 
-                           header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PSQS_file_paths)) {
-  # file_path = paste0('REPORT_OUTPUT_DIR/', PSQS_file_paths[i,2])
-  file_path = PSQS_file_paths[i,2]
-  psqs_df = read.csv(file_path,
-                     sep='\t', header=TRUE, stringsAsFactors = FALSE) 
-  psqs_df$sample_id = rep(PSQS_file_paths[i,1], nrow(psqs_df))
-  PSQS_df = rbind(PSQS_df, psqs_df)
-}
+```{r 'session info'}
+sessionInfo()
 ```
 
-
-```{r}
-max_phred = max(PSQS_df$X.Quality) + 5
-hchart(PSQS_df, "line", hcaes(x = X.Quality, y = Count, group = sample_id)) %>%
-  hc_title(
-    text = "Per Sequence Quality Score"
-  ) %>%
-  hc_xAxis(
-    title = list(text = "Mean Sequence Quality Score"),
-    min = 0,
-    max = max_phred,
-    plotLines = list(
-      list(label = list(text = "Phred Score = 27"),
-           width = 2,
-           dashStyle = "dash",
-           color = "green",
-           value = 27),
-      list(label = list(text = "Phred Score = 20"),
-           width = 2,
-           color = "red",
-           value = 20)
-    )
-  ) %>% 
-  hc_exporting(enabled = TRUE)
-```
-
-
-## Per Sequence GC Content
-
-
-```{r}
-PSGC_df = data.frame()
-PSGC_file_paths = read.csv('PSGC_file_paths.txt', 
-                           header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PSGC_file_paths)) {
-  # file_path = paste0('REPORT_OUTPUT_DIR/', PSGC_file_paths[i,2])
-  file_path = PSGC_file_paths[i,2]
-  psgc_df = read.csv(file_path,
-                     sep='\t', header=TRUE, stringsAsFactors = FALSE) 
-  psgc_df$sample_id = rep(PSGC_file_paths[i,1], nrow(psgc_df))
-  PSGC_df = rbind(PSGC_df, psgc_df)
-}
-```
-
-
-```{r}
-max_phred = max(PSGC_df$Count) + 5
-hchart(PSGC_df, "line", hcaes(x = X.GC.Content, y = Count, group = sample_id)) %>%
-  hc_title(
-    text = "Per Sequence GC Content"
-  ) %>%
-  hc_xAxis(
-    title = list(text = "% GC")
-  ) %>%
-  hc_exporting(enabled = TRUE)
-```
-
-
-## Per Base Sequence Content
-
-```{r}
-PBSC_df = data.frame()
-PBSC_file_paths = read.csv('PBSC_file_paths.txt',
-                           header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBSC_file_paths)) {
-  # file_path = paste0('REPORT_OUTPUT_DIR/', PBSC_file_paths[i,2])
-  file_path = PBSC_file_paths[i,2]
-  pbsc_df = read.csv(file_path,
-                     sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
-    mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
-           Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
-  (function (df) {
-    df1 = select(df, -Base2)
-    df2 = select(df, -Base1) %>% filter(Base2 != '')
-    colnames(df1) = c(colnames(df1)[1:5], 'Base')
-    colnames(df2) = c(colnames(df2)[1:5], 'Base')
-    res = rbind(df1, df2) %>% arrange(Base)
-    return(res)
-  })
-  pbsc_df$sample_id = rep(PBSC_file_paths[i,1], nrow(pbsc_df))
-  PBSC_df = rbind(PBSC_df, pbsc_df)
-}
-```
-
-
-```{r out.width="100%"}
-PBSC_df_2 = select(PBSC_df, -X.Base) %>%
-  melt(id = c('Base', 'sample_id'), value.name = 'base_percentage')
-p = ggplot(data = PBSC_df_2, aes(x = Base, y = base_percentage, group = variable, color = variable)) +
-  geom_line() +
-  facet_wrap(~ sample_id)
-ggplotly(p)
-```
-
-
-## References
-
-* Andrews, Simon. "FastQC: a quality control tool for high throughput sequence data." (2010): 175-176.
-* Goecks, Jeremy, Anton Nekrutenko, and James Taylor. "Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences." Genome biology 11.8 (2010): R86.
-* Afgan, Enis, et al. "The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update." Nucleic acids research (2016): gkw343.
-* Highcharts. https://www.highcharts.com/. (access by May 26, 2017).
-* R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
-* Joshua Kunst (2017). highcharter: A Wrapper for the 'Highcharts' Library. R package version 0.5.0. https://CRAN.R-project.org/package=highcharter
-* Carson Sievert, Chris Parmer, Toby Hocking, Scott Chamberlain, Karthik Ram, Marianne Corvellec and Pedro Despouy (2017). plotly: Create Interactive Web Graphics via 'plotly.js'. R package version 4.6.0. https://CRAN.R-project.org/package=plotly